The goods and package transport industry can be divided into several segments, each offering services that satisfy different customer needs. At the one end of the transport industry spectrum, a single customer order may fill an entire carrier. At the other end of the spectrum are parcel delivery services, where a carrier transports hundreds of individual small loads or packages. The present invention is focused on the segment of the transport industry that falls somewhere between these two extremes. In particular, it addresses the transport problems associated with transporting large orders in large moving vans, as commonly encountered, for example, in the transport of household goods. The present system specifically addresses the situation where a van is assigned to pick up several orders from different customer locations and deliver each order to a different destination. The remainder of this document will discuss application of the present invention to this particular segment of the transport industry, hereinafter referred to as "the moving industry."
In the moving industry, a customer places an order to move goods from an origin to a destination. A van is assigned to pick up the order and deliver it to the requested destination. Typically, most orders occupy only a fraction of the available space on the van and multiple orders must be consolidated to form a full load. Within the moving industry, it is common to combine on an average approximately four to ten orders into a load for a single van.
If the assigned van cannot pick up the order, a local van picks up the order from the customer and stores it in a warehouse. This process is known as a "pick up and store." Later, an assigned van picks up the order from the warehouse and delivers it to the destination. Pick up and store involves extra expenses and double handling and is generally discouraged. However, this technique can be used to reduce variation in demand for vans. During slow periods, vans are assigned to deliver pick up and store orders. During busy periods, the technique can reduce the overall demand for vans. However, use of pick up and store procedures is always limited by customer scheduling constraints.
The volume of orders vary daily, weekly, and seasonally. To add to the complexity of the problem, several kinds of vans may be used. Vans can be owned outright or leased on a short term basis. The matching of a van to an order is based on the type of load and the distance it has to be carried.
Transportation companies turn away tonnage each year, despite the fact that their average van utilization is low. This is because vans are not in the right place at the right time and the load consolidation strategy, which combines smaller orders into a van load, does not maximize van utilization.
In essence, the problems is one of meeting customer scheduling demands, while minimizing the operating costs. Although, the problem sounds simple, it is complicated by the business dynamics, such as, last-minute orders, changes to existing orders, order cancellations, van delays, van breakdowns, etc. The equation is further complicated due to restrictions imposed by the Government (i.e., maximum time drivers can be on the road per day, inter and intra state regulations, etc.).
Traditional approaches such as Linear Programming cannot provide real-time decision support. Because of constant fluctuations of orders and lack of precise information on the position of vans, planning using linear programming is impractical.